Data processing systems for fulfilling data subject access requests and related methods

ABSTRACT

Responding to a data subject access request includes receiving the request and identifying the requestor and source. In response to identifying the requestor and source, a computer processor determines whether the data subject access request is subject to fulfillment constraints, including whether the requestor or source is malicious. If so, then the computer processor denies the request or requests a processing fee prior to fulfillment. If not, then the computer processor fulfills the request.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.16/786,196, filed Feb. 10, 2020, which is a continuation of U.S. patentapplication Ser. No. 16/512,011, filed Jul. 15, 2019, now U.S. Pat. No.10,558,821, issued Feb. 11, 2020, which is a continuation of U.S. patentapplication Ser. No. 16/226,290, filed Dec. 19, 2018, now U.S. Pat. No.10,354,089, issued Jul. 16, 2019, which is a continuation of U.S. patentapplication Ser. No. 16/054,672, filed Aug. 3, 2018, now U.S. Pat. No.10,169,609, issued Jan. 1, 2019, which claims priority from U.S.Provisional Patent Application Ser. No. 62/547,530, filed Aug. 18, 2017,and which is also a continuation-in-part of U.S. patent application Ser.No. 15/996,208, filed Jun. 1, 2018, now U.S. Pat. No. 10,181,051, issuedJan. 15, 2019, which claims priority from U.S. Provisional PatentApplication Ser. No. 62/537,839, filed Jul. 27, 2017, and is also acontinuation-in-part of U.S. patent application Ser. No. 15/853,674,filed Dec. 22, 2017, now U.S. Pat. No. 10,019,597, issued Jul. 10, 2018,which claims priority from U.S. Provisional Patent Application Ser. No.62/541,613, filed Aug. 4, 2017, and is also a continuation-in-part ofU.S. patent application Ser. No. 15/619,455, filed Jun. 10, 2017, nowU.S. Pat. No. 9,851,966, issued Dec. 26, 2017, which is acontinuation-in-part of U.S. patent application Ser. No. 15/254,901,filed Sep. 1, 2016, now U.S. Pat. No. 9,729,583, issued Aug. 8, 2017,which claims priority from: (1) U.S. Provisional Patent Application Ser.No. 62/360,123, filed Jul. 8, 2016; (2) U.S. Provisional PatentApplication Ser. No. 62/353,802, filed Jun. 23, 2016; and (3) U.S.Provisional Patent Application Ser. No. 62/348,695, filed Jun. 10, 2016.The disclosures of all of the above patent applications are herebyincorporated herein by reference in their entirety.

BACKGROUND

Over the past years, privacy and security policies, and relatedoperations have become increasingly important. Breaches in security,leading to the unauthorized access of personal data (which may includesensitive personal data) have become more frequent among companies andother organizations of all sizes. Such personal data may include, but isnot limited to, personally identifiable information (PII), which may beinformation that directly (or indirectly) identifies an individual orentity. Examples of PII include names, addresses, dates of birth, socialsecurity numbers, and biometric identifiers such as a person'sfingerprints or picture. Other personal data may include, for example,customers' Internet browsing habits, purchase history, or even theirpreferences (e.g., likes and dislikes, as provided or obtained throughsocial media).

Many organizations that obtain, use, and transfer personal data,including sensitive personal data, have begun to address these privacyand security issues. To manage personal data, many companies haveattempted to implement operational policies and processes that complywith legal and industry requirements. However, there is an increasingneed for improved systems and methods to manage personal data in amanner that complies with such policies.

SUMMARY

It should be appreciated that this Summary is provided to introduce aselection of concepts in a simplified form that are further describedbelow in the Detailed Description. This Summary is not intended to beused to limit the scope of the claimed subject matter.

A computer-implemented method for responding to a data subject accessrequest is provided. According to one aspect, one or more computerprocessors receive a data subject access request from a requestor, therequest having one or more pieces of personal data. The computerprocessor identifies the requestor based at least in part the personaldata. The computer processor identifies the source of the request basedat least in part on the requestor or source data associated with thedata subject access request. In response to identifying the requestorand the source of the data subject access request the computer processordetermines whether the data subject access request is subject to one ormore response fulfillment constraints associated with the requestor orthe source by determining whether the requestor is a malicious requestoror whether the source is a malicious source. In response to determiningthat the data subject access request is subject to one or more responsefulfillment constraints, the computer processor denies the data subjectaccess request, or requests one or more processing fees prior tofulfilling the request. In response to determining that the data subjectaccess request is not subject to one or more response fulfillmentconstraints, the computer processor fulfills the data subject accessrequest.

According to another aspect, a computer-implemented method forresponding to a data subject access request includes receive a datasubject access request from a requestor, the request having one or morerequest parameters from a requestor at a source. In response toreceiving the data subject access request, one or more computerprocessors retrieve fulfillment constraint data associated with the datasubject access request from a repository server corresponding to anumber of data subject access requests from a number of requestors and anumber of sources. The computer processor determines whether therequestor is a malicious requestor or whether the source is a malicioussource based on the fulfillment constraint data and the requestparameters. In response to determining that the requestor is a maliciousrequestor or that the source is a malicious source, the computerprocessor determines whether the data subject access request is subjectto one or more fulfillment constraints. If so, the computer processordenies the data subject access request or requests one or moreprocessing fees prior to fulfilling the request.

According to yet another aspect, a computer-implemented method forresponding to a data subject access request includes one or morecomputer processors receiving a data subject access request with one ormore pieces of personal data associated with a requestor. The computerprocessor identifies the requestor based at least in part on the requestparameters. In response to identifying the requestor, the computerprocessor retrieves fulfillment constraint data associated with therequestor. The computer processor determines whether the requestor ispotentially malicious based on the fulfillment constraint data. Inresponse to determining that the requestor is potentially malicious, thecomputer processor determines whether the data subject access request issubject to one or more fulfillment constraints. If so, the computerprocessor denies the data subject access request or requests one or moreprocessing fees prior to fulfilling the request. If not, the computerprocessor fulfills the data subject access request.

The features, functions, and advantages that have been discussed can beachieved independently in various embodiments of the present disclosureor may be combined in yet other embodiments, further details of whichcan be seen with reference to the following description and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of a data subject access request fulfillment systemare described below. In the course of this description, reference willbe made to the accompanying drawings, which are not necessarily drawn toscale, and wherein:

FIGS. 1-6 depict various exemplary screen displays and user interfacesthat a user of various embodiments of the system may encounter.

FIG. 7 depicts a data subject request processing and fulfillment systemaccording to particular embodiments.

FIG. 8 is a schematic diagram of a computer (such as the data modelgeneration server 110, or data model population server 120) that issuitable for use in various embodiments of the data subject requestprocessing and fulfillment system shown in FIG. 7.

FIGS. 9-49 are computer screen shots that demonstrate the operation ofvarious embodiments.

FIG. 50 depicts a data subject access request response and fulfillmentconstraint determination system according to particular embodiments.

FIG. 51 depicts a flow chart showing an example of acomputer-implemented data processing method for responding to a datasubject access request according to particular embodiments.

FIG. 52 depicts a flow chart showing an example of acomputer-implemented data processing method for responding to a datasubject access request while maintaining fulfillment constraint dataaccording to particular embodiments.

DETAILED DESCRIPTION

Various embodiments now will be described more fully hereinafter withreference to the accompanying drawings. It should be understood that theinvention may be embodied in many different forms and should not beconstrued as limited to the embodiments set forth herein. Rather, theseembodiments are provided so that this disclosure will be thorough andcomplete, and will fully convey the scope of the invention to thoseskilled in the art. Like numbers refer to like elements throughout.

Overview

In various embodiments, an organization, corporation, etc. may berequired to provide information requested by an individual for whom theorganization stores personal data. As a particular example, anorganization may be required to provide an individual with a listing of,for example: (1) any personal data that the organization is processingfor an individual, (2) an explanation of the categories of data beingprocessed and the purpose of such processing; (3) categories of thirdparties to whom the data may be disclosed; (4) etc. In particularembodiments, when processing a data subject access request (e.g., arequest for such information), a data subject access request fulfillmentsystem may be configured to verify an identity of the requestor (e.g., adata subject) prior to processing the request.

In various embodiments, a data subject access request fulfillment systemmay be implemented in the context of any suitable privacy managementsystem that is configured to ensure compliance with one or more legal orindustry standards related to the collection and/or storage of privateinformation (e.g., such as personal data). In various embodiments, aparticular organization, sub-group, or other entity may initiate aprivacy campaign or other activity (e.g., processing activity) as partof its business activities. In such embodiments, the privacy campaignmay include any undertaking by a particular organization (e.g., such asa project or other activity) that includes the collection, entry, and/orstorage (e.g., in computer memory) of any personal data associated withone or more individuals (e.g., data subjects). In particularembodiments, a privacy campaign may include any project undertaken by anorganization that includes the use of personal data, or any otheractivity that could have an impact on the privacy of one or moreindividuals.

In any embodiment described herein, personal data may include, forexample: (1) the name of a particular data subject (which may be aparticular individual); (2) the data subject's address; (3) the datasubject's telephone number; (4) the data subject's e-mail address; (5)the data subject's social security number; (6) information associatedwith one or more of the data subject's credit accounts (e.g., creditcard numbers); (7) banking information for the data subject; (8)location data for the data subject (e.g., their present or pastlocation); (9) internet search history for the data subject; and/or (10)any other suitable personal information, such as other personalinformation discussed herein. In particular embodiments, such personaldata may include one or more cookies (e.g., where the individual isdirectly identifiable or may be identifiable based at least in part oninformation stored in the one or more cookies).

Various privacy and security policies (e.g., such as the EuropeanUnion's General Data Protection Regulation, and other such policies) mayprovide data subjects (e.g., individuals, organizations, or otherentities) with certain rights related to the data subject's personaldata that is collected, stored, or otherwise processed by anorganization. These rights may include, for example: (1) a right toobtain confirmation of whether a particular organization is processingtheir personal data; (2) a right to obtain information about the purposeof the processing (e.g., one or more reasons for which the personal datawas collected); (3) a right to obtain information about one or morecategories of data being processed (e.g., what type of personal data isbeing collected, stored, etc.); (4) a right to obtain information aboutone or more categories of recipients with whom their personal data maybe shared (e.g., both internally within the organization or externally);(5) a right to obtain information about a time period for which theirpersonal data will be stored (e.g., or one or more criteria used todetermine that time period); (6) a right to obtain a copy of anypersonal data being processed (e.g., a right to receive a copy of theirpersonal data in a commonly used, machine-readable format); (7) a rightto request erasure (e.g., the right to be forgotten), rectification(e.g., correction or deletion of inaccurate data), or restriction ofprocessing of their personal data; and (8) any other suitable rightsrelated to the collection, storage, and/or processing of their personaldata (e.g., which may be provided by law, policy, industry ororganizational practice, etc.).

As may be understood in light of this disclosure, a particularorganization may undertake a plurality of different privacy campaigns,processing activities, etc. that involve the collection and storage ofpersonal data. In some embodiments, each of the plurality of differentprocessing activities may collect redundant data (e.g., may collect thesame personal data for a particular individual more than once), and maystore data and/or redundant data in one or more particular locations(e.g., on one or more different servers, in one or more differentdatabases, etc.). In this way, a particular organization may storepersonal data in a plurality of different locations which may includeone or more known and/or unknown locations. As such, complying withparticular privacy and security policies related to personal data (e.g.,such as responding to one or more requests by data subjects related totheir personal data) may be particularly difficult (e.g., in terms ofcost, time, etc.). In particular embodiments, the data subject accessrequest fulfillment system may utilize one or more data model generationand population techniques to create a centralized data map with whichthe system can identify personal data stored, collected, or processedfor a particular data subject, a reason for the processing, and anyother information related to the processing.

In particular embodiments, the data subject access request fulfillmentsystem is configured to: (1) receive a data subject access request froma data subject, the data subject access request comprising one or morerequests related to the one or more rights described above (e.g., arequest for a copy of the data subject's personal data, a requestregarding how long personal data associated with the data subject isbeing stored by the system, etc.); (2) process the request; and (3)fulfill the request based at least in part on one or more requestparameters.

FIGS. 1-2 depict exemplary screen displays that a user may view whensubmitting a data subject access request (e.g., exemplary userinterfaces for submitting a data subject access request). As shown inFIG. 1, a website associated with a particular organization may includea user-selectable indicia for submitting a privacy-related request. Auser desiring to make such a request may select the indicia in order toinitiate the data subject access request process.

FIG. 2 depicts an exemplary data subject access request form in both anunfilled and filled out state. As shown in this figure, the system mayprompt a user to provide information such as, for example: (1) what typeof requestor the user is (e.g., employee, customer, etc.); (2) what therequest involves (e.g., requesting info, opting out, deleting data,updating data, etc.); (3) first name; (4) last name; (5) email address;(6) telephone number; (7) home address; (8) one or more other pieces ofidentifying information; and/or (9) one or more details associated withthe request. As will be discussed more fully below, the system may beconfigured to utilize one or more pieces of information provided by thedata subject when processing and fulfilling the data subject accessrequest.

Various embodiments of a data subject access request fulfillment systemare described more fully below.

Automatic Identity Validation Systems

In particular embodiments, when processing a data subject accessrequest, the system may be configured to verify an identity of the datasubject prior to processing the request (e.g., or as part of theprocessing step). In various embodiments, confirming the identity of thedata subject may, for example, limit a risk that a third-party or otherentity may gain unlawful or unconsented to access to the requestor'spersonal data. The system may, for example, limit processing andfulfillment of requests relating to a particular data subject torequests that are originated by (e.g., received from) the particulardata subject. When processing a data subject access request, the systemmay be configured to use all reasonable measures to verify the identityof the data subject who requests access (e.g., in particular in thecontext of online services and online identifiers). In particularembodiments, the system is configured to substantially automaticallyvalidate an identity of a data subject when processing the data subjectaccess request.

For example, in particular embodiments, the system may be configured tosubstantially automatically (e.g., automatically) authenticate and/orvalidate an identity of a data subject using any suitable technique.These techniques may include, for example: (1) one or more credit-basedand/or public- or private-information-based verification techniques; (2)one or more company verification techniques (e.g., in the case of abusiness-to-business data subject access request); (3) one or moretechniques involving integration with a company's employeeauthentication system; (4) one or more techniques involving a company's(e.g., organization's) consumer portal authentication process; (5) etc.Various exemplary techniques for authenticating a data subject arediscussed more fully below.

In particular embodiments, when authenticating a data subject (e.g.,validating the data subject's identity), the system may be configured toexecute particular identity confirmation steps, for example, byinterfacing with one or more external systems (e.g., one or morethird-party data aggregation systems). For example, the system, whenvalidating a data subject's identity, may begin by verifying that aperson with the data subject's name, address, social security number, orother identifying characteristic (e.g., which may have been provided bythe data subject as part of the data subject access request) actuallyexists. In various embodiments, the system is configured to interfacewith (e.g., transmit a search request to) one or more credit reportingagencies (e.g., Experian, Equifax, TransUnion, etc.) to confirm that aperson with one or more characteristics provided by the data subjectexists. The system may, for example, interface with such creditreporting agencies via a suitable plugin (e.g., software plugin).Additionally, there might be a verification on behalf of a trustedthird-party system (e.g., the controller).

In still other embodiments, the system may be configured to utilize oneor more other third-party systems (e.g., such as LexisNexis, IDology,RSA, etc.), which may, for example, compile utility and phone bill data,property deeds, rental agreement data, and other public records forvarious individuals. The system may be configured to interface with oneor more such third-party systems to confirm that a person with one ormore characteristics provided by the data subject exists.

After the step of confirming the existence of a person with the one ormore characteristics provided by the data subject, the system may beconfigured to confirm that the person making the data subject accessrequest is, in fact, the data subject. The system may, for example,verify that the requestor is the data subject by prompting the requestorto answer one or more knowledge-based authentication questions (e.g.,out-of-wallet questions). In particular embodiments, the system isconfigured to utilize one or more third-party services as a source ofsuch questions (e.g., any of the suitable third-party sources discussedimmediately above). The system may use third-party data from the one ormore third-party sources to generate one or more questions. These one ormore questions may include questions that a data subject should know ananswer to without knowing the question ahead of time (e.g., one or moreprevious addresses, a parent or spouse name and/or maiden name, etc.).

FIG. 3 depicts an exemplary identity verification questionnaire. As maybe understood from this figure, an identity verification questionnairemay include one or more questions whose responses include data that thesystem may derive from one or more credit agencies or other third-partydata aggregation services (e.g., such as previous street addresses,close associates, previous cities lived in, etc.). In particularembodiments, the system is configured to provide these one or morequestions to the data subject in response to receiving the data subjectaccess request. In other embodiments, the system is configured to promptthe data subject to provide responses to the one or more questions at alater time (e.g., during processing of the request). In particular otherembodiments, the system is configured to substantially automaticallycompare one or more pieces of information provided as part of the datasubject access request to one or more pieces of data received from athird-party data aggregation service in order to substantiallyautomatically verify the requestor's identity.

In still other embodiments, the system may be configured to prompt arequestor to provide one or more additional pieces of information inorder to validate the requestor's identity. This information mayinclude, for example: (1) at least a portion of the requestor's socialsecurity number (e.g., last four digits); (2) a name and/or place ofbirth of the requestor's father; (3) a name, maiden name, and/or placeof birth of the requestor's mother; and/or (4) any other informationwhich may be useful for confirming the requestor's identity (e.g., suchas information available on the requestor's birth certificate). In otherembodiments, the system may be configured to prompt the requestor toprovide authorization for the company to check the requestor's socialsecurity or other private records (e.g., credit check authorization,etc.) to obtain information that the system may use to confirm therequestor's identity. In other embodiments, the system may prompt theuser to provide one or more images (e.g., using a suitable mobilecomputing device) of an identifying document (e.g., a birth certificate,social security card, driver's license, etc.).

The system may, in response to a user providing one or more responsesthat matches information that the system receives from one or morethird-party data aggregators or through any other suitable background,credit, or other search, substantially automatically authenticate therequestor as the data subject. The system may then continue processingthe data subject's request, and ultimately fulfill their request.

In particular embodiments, such as embodiments in which the requestorincludes a business (e.g., as in a business to business data subjectaccess request), the system may be configured to authenticate therequesting business using one or more company verification techniques.These one or more company validation techniques may include, forexample, validating a vendor contract (e.g., between the requestingbusiness and the company receiving the data subject access request);receiving a matching token, code, or other unique identifier provided bythe company receiving the data subject access request to the requestingbusiness; receiving a matching file in possession of both the requestingbusiness and the company receiving the data subject access request;receiving a signed contract, certificate (e.g., digital or physical), orother document memorializing an association between the requestingbusiness and the company receiving the data subject access request;and/or any other suitable method of validating that a particular requestis actually made on behalf of the requesting business (e.g., byrequesting the requesting business to provide one or more pieces ofinformation, one or more files, one or more documents, etc. that mayonly be accessible to the requesting business).

In other embodiments, the system may be configured to authenticate arequest via integration with a company's employee or customer (e.g.,consumer) authentication process. For example, in response to receivinga data subject access request that indicates that the data subject is anemployee of the company receiving the data subject access request, thesystem may be configured to prompt the employee to login to thecompany's employee authentication system (e.g., Okta, Azure, AD, etc.)In this way, the system may be configured to authenticate the requestorbased at least in part on the requestor successfully logging into theauthentication system using the data subject's credentials. Similarly,in response to receiving a data subject access request that indicatesthat the data subject is a customer of the company receiving the datasubject access request, the system may be configured to prompt thecustomer to login to an account associated with the company (e.g., via aconsumer portal authentication process). In a particular example, thismay include, for example, an Apple ID (for data subject access requestsreceived by Apple). In this way, the system may be configured toauthenticate the requestor based at least in part on the requestorsuccessfully logging into the authentication system using the datasubject's credentials. In some embodiments, the system may be configuredto require the requestor to login using two-factor authentication orother suitable existing employee or consumer authentication process.

Data Subject Request Fulfillment Constraints

In various embodiments, a particular organization may not be required torespond to a data subject access request that originates from (e.g., isreceived from) a malicious requestor or source. A malicious requestor orsource may include, for example: a requestor (e.g., an individual) thatsubmits excessive or redundant data subject access requests; a requestorwho is a disgruntled employee that was previously and not currentlyemployed by the company receiving the data subject access request thatis submitting such requests to tie up the company's resourcesunnecessarily; a group of requestors such as researchers, professors,students, NGOs, etc. that submit a plurality of requests for reasonsother than those reasons provided by policy, law, etc.; a competitor ofthe company receiving the data subject access request that is submittingsuch requests to tie up the company's resources unnecessarily; a groupof requestors originating from a particular geographic region (e.g., acountry) that may submit excessive data subject access requests todisrupt the company's operations or tie up the company's resourcesunnecessarily for economic or other reasons; a group of requestorsassociated with a particular political organization that may submitexcessive data subject access requests to expend the company's resourcesfor economic or retaliatory reasons; a group of requestors associatedwith a particular protesting organization (e.g., a group protesting thecompany, the company's employees, or the any entities affiliated withthe company for any reason) that may submit excessive data subjectaccess requests to expend the company's resources; a terrorist or otherorganization that may spam requests to disrupt the company's operationand response to valid requests; and/or any other request that may falloutside the scope of valid requests made for reasons proscribed bypublic policy, company policy, or law.

In particular embodiments, the system is configured to maintain a“blacklist” of such malicious requestors. As will be described in detailbelow, this virtual blacklist may include fulfillment constraint datathat may be cross-referenced upon receipt of a data subject accessrequest to determine if the data subject access request is subject toone or more response fulfillment constraints. If the data subject accessrequest is subject to one or more response fulfillment constraints, thenthe system may take action on the request according to one or morelimitations.

Looking now at FIGS. 50-52, illustrative examples for processing datasubject access requests will be described with respect to theutilization of one or more response fulfillment constraints. FIG. 50shows a visualization of a data subject access request response andfulfillment constraint determination system 5000 according to variousembodiments. For clarity purposes, an overview of the system 5000 willbe provided prior to a detailed discussion of the various actions andcomponents of the system 5000 and corresponding process.

According to various embodiments, a Data Subject Access Request (DSAR)102 is submitted by a requestor and received at a DSAR Processing andFulfillment Server 170. The DSAR 102 may be submitted and authenticatedin the manner described above. The DSAR Processing and FulfillmentServer 170 may utilize one or more databases 140 and/or one or morethird party servers 160 (discussed in greater detail below with respectto the example system architecture and FIG. 7 below) to determinewhether any Fulfillment Constraint Data 106 exists corresponding to theRequestor 112 of the DSAR 102, the Source 114 of the DSAR 102, or OtherFulfillment Constraint Data Criteria 116 related to the DSAR 102.According to particular embodiments, the one or more databases 140and/or one or more third party servers 160 may include a Third PartyRepository Server 104 that serves as a central repository for storingand accessing both Personal Data 108 that is the target of the DSAR 102and Fulfillment Constraint Data 106 that may be used to impose one ormore limitations on any fulfillment of the DSAR 102. By utilizing aThird Party Repository Server 104, the system may analyze global data(e.g., all data collected for a plurality of companies that utilize thedata subject access request fulfillment system) to generate theFulfillment Constraint Data 106.

After verifying the existence of any Fulfillment Constraint Data 106,the DSAR Processing and Fulfillment Server 170 takes action, either by aFulfillment Action 180 or a Deny Action 190. The action taken by theDSAR Processing and Fulfillment Server 170 may be subject to One or MoreLimitations 192 (indicated in FIG. 50 by the box outlined with brokenlines) depending on the outcome of the search for Fulfillment ConstraintData 106. Specifically, the One or More Limitations 192 may includefulfilling the DSAR 102 conditional upon payment of a processing fee, ordenying or rejecting the DSAR 102. Action taken by the DSAR Processingand Fulfillment Server 170 that is subject to One or More Limitations192 results in a notification action 194 in which the requestorassociated with the DSAR 102 is notified as to the One or MoreLimitations 192 and the reasoning behind the One or More Limitations192.

Looking at the system 5000 now in greater detail, the DSAR 102 may besubmitted using the exemplary data subject access request form shown anddescribed above with respect to FIGS. 1 and 2. The system may prompt theuser to provide information such as, for example: (1) what type ofrequestor the user is (e.g., employee, customer, etc.); (2) what therequest involves (e.g., requesting info, opting out, deleting data,updating data, etc.); (3) first name; (4) last name; (5) email address;(6) telephone number; (7) home address; (8) one or more other pieces ofidentifying information; and/or (9) one or more details associated withthe request. According to various embodiments, the requestor mayadditionally be prompted to provide information regarding the number ofDSARs 102 previously submitted and corresponding dates, as well as anyadditional employment or organizational affiliation information thatcould subject the DSAR 102 to one or more response fulfillmentconstraints. While the system may not rely solely on the informationprovided by the requestor in determining whether one or more responsefulfillment constraints apply to the DSAR 102, time and resources may besaved if the information input by the requestor triggers a responsefulfillment constraint without necessitating a search for FulfillmentConstraint Data 106.

According to various embodiments, the system is configured to track arequestor and a source associated with each DSAR 102 and analyze eachDSAR 102 to identify requestors and/or sources from which: (1) thecompany receives a large volume of requests; (2) the company receives alarge number of repeat requests; (3) the company receives a request froma requestor or source for which the company does not legally have torespond, or have to respond at no cost. The sources may include, forexample: (1) one or more particular IP addresses; (2) one or moreparticular domains; (3) one or more particular countries; (4) one ormore particular institutions; (5) one or more particular geographicregions; (6) one or more political group; and/or (7) one or moreprotesting group. In response to analyzing the sources of the requests,the system may identify one or more requestors or sources that may bemalicious (e.g., are submitting excessive requests). For the purposes ofthis disclosure, a malicious requestor or source of a DSAR 102encompasses any DSAR 102 that falls outside of the guidelines andregulations requiring a free response to a DSAR 102.

As an example, the system may be configured to fulfill data subjectaccess requests for the purpose of providing a data subject withinformation regarding what data the company collects and for whatpurpose. A typical DSAR 102 may be made so that the data subject canensure that the company is collecting data for lawful reasons. As such,the system may be configured to identify requestors and other sources ofdata requests that are made for other reasons (e.g., a malicious reasonor one or more reasons that would not obligate the company to respond tothe request). These reasons may include, for example, malicious or otherreasons. One example includes requests made for research by an academicinstitution by one or more students or professors. While not maliciousin the traditional sense, these requests may be categorized as maliciousby the system since they tie up a large amount of company resources anddo not require a free response by law. Anticompetitive requests by oneor more competitors may be maliciously submitted with the intention toexpend company time and resources. Requests by disgruntled formeremployees may be submitted for nefarious reasons. Requests from aparticular country or geographic region may have malicious interests intying up the resources of the company by submitting excessive orfrivolous DSARs 102. Requests from a particular political group may bemade with malicious interests in tying up the resources of the company.Similarly, one or more protesting groups or organizations may have thepurpose of submitting one or more DSARs 102 to expend time and resourcesof the company and its employees. It should be appreciated that thedisclosure herein encompasses any response fulfillment constraints basedon the submission of any DSAR 102 that is not submitted for lawful,legitimate reasons.

In various embodiments, the system is configured to maintain a databaseof the identified one or more requestors and sources (e.g., in computermemory). In particular embodiments, the database may store a listing ofidentities, data sources, etc. that have been found (e.g., by thesystem) to result in one or more response fulfillment constraints thatlead to a denial of the request or a fulfillment subject to one or moreprocessing fees. This listing is stored in One or More Databases 140 orreside on One or More Third Party Servers 160 (FIG. 7, discussed below)as Fulfillment Constraint Data 106. As mentioned above, in oneparticular embodiment, the in One or More Databases 140 or One or MoreThird Party Servers 160 includes a Third Party Repository Server 104, asshown in FIG. 50.

The Third Party Repository Server 104 acts as a central data-storagerepository (e.g., one or more servers, databases, etc.), for thecentralized storage of personally identifiable information (PII) and/orPersonal Data 108 for one or more particular data subjects. Inparticular embodiments, the Third Party Repository Server 104 may enablethe system to populate one or more data models (e.g., using one or moresuitable techniques described herein) substantially on-the-fly (e.g., asthe system collects, processes, stores, etc. Personal Data 108 regardinga particular data subject). In this way, in particular embodiments thesystem is configured to maintain a substantially up-to-date data modelfor a plurality of data subjects (e.g., each particular data subject forwhom the system collects, processes, stores, etc. Personal Data 108).The system may then be configured to substantially automatically respondto one or more data access requests by a data subject (e.g., individual,entity, organization, etc.), for example, using the substantiallyup-to-date data model.

A particular organization may undertake a plurality of different privacycampaigns, processing activities, etc. that involve the collection andstorage of Personal Data 108. In some embodiments, each of the pluralityof different processing activities may collect redundant data (e.g., maycollect the same Personal Data 108 for a particular individual more thanonce), and may store data and/or redundant data in one or moreparticular locations (e.g., on one or more different servers, in one ormore different databases, etc.). In this way, a particular organizationmay store Personal Data 108 in a plurality of different locations whichmay include one or more known and/or unknown locations. As such,complying with particular privacy and security policies related toPersonal Data 108 (e.g., such as responding to one or more requests bydata subjects related to their Personal Data 108) may be particularlydifficult (e.g., in terms of cost, time, etc.). Accordingly, utilizingand maintaining a Third Party Repository Server 104 for PII may enablethe system to more quickly and accurately respond to DSARs 102 and otherrequests related to collected, stored, and processed Personal Data 108.

In various embodiments, a Third Party Repository Server 104 isconfigured to facilitate the receipt and centralized storage of PersonalData 108 for each of a plurality of respective data subjects. Inparticular embodiments, the system may be configured to: (1) receivePersonal Data 108 associated with a particular data subject (e.g., acopy of the data, a link to a location of where the data is stored,etc.); and (2) store the Personal Data 108 in a suitable data format(e.g., a data model, a reference table, etc.) for later retrieval.

In particular embodiments, the Third Party Repository Server 104 isconfigured to: (1) receive an indication that a first party system(e.g., entity) has collected and/or processed a piece of Personal Data108 for a data subject; (2) determine a location in which the firstparty system has stored the piece of Personal Data 108; (3) optionallydigitally store (e.g., in computer memory) a copy of the piece ofPersonal Data 108 and associate, in memory, the piece of Personal Data108 with the data subject; and (4) optionally digitally store anindication of the storage location utilized by the first party systemfor the piece of Personal Data 108. In particular embodiments, thesystem is configured to provide a centralized database, for eachparticular data subject, of any Personal Data 108 processed and/orcollected by a particular entity.

Referring again to FIG. 50, whether at a central repository such as theThird Party Repository Server 104, or at One or More Databases 140 orOne or More Third Party Servers 160, the system is configured tomaintain a listing of Fulfillment Constraint Data 106. This FulfillmentConstraint Data 106 may include, for example, one or more Requestors 112identified (e.g., by a name, an organization, or other entity) assubmitting excessive or other malicious DSARs 102, one or more Sources114 of malicious DSAR 102 submissions, and/or Other FulfillmentConstraint Data Criteria 116 related to malicious submissions of DSARs102. An example of Fulfillment Constraint Data 106 related to theidentities of one or more Requestors 112 includes the number of requestspreviously submitted by an individual or organization and any relatedinformation, such as the dates and of any previous requests andinformation regarding the source of the requests (e.g., geographiclocation, domains and IP addresses). Other examples may include theidentities of any objectionable requestors, such as disgruntledemployees or individuals with a history of targeting the company withmalicious attacks of any sort.

In particular embodiments, the system may, for example, maintain adatabase (e.g., in computer memory) of former employees that are nolonger employed by the company. When comparing the identity of therequesting party with the Requestor 112 identities and correspondinginformation stored as Fulfillment Constraint Data 106 in the Third PartyRepository Server 104, DSAR Processing and Fulfillment Server 170 maydetermine that being a former employee alone is not enough to subjectthe DSAR 102 to one or more response fulfillment constraints,specifically imposing one or more limitations such as a fulfillment ofthe request subject to a processing fee or denial of the request.Rather, the DSAR Processing and Fulfillment Server 170 may impose one ormore limitations only if a former employee is further flagged oridentified with a malicious history of requests (e.g., excessiverequests or requests exceeding a threshold number) or potential formalicious requests. With respect to determining that a requestorpossesses a potential for malicious requests, this potential may bestored as a rating or value assigned to the Requestor 112 in theFulfillment Constraint Data 106 based on historical actions or specialcircumstances with respect to the requestor's departure from thecompany. It should be appreciated that any criteria may be used todetermine that the Requestor 112 is subject to one or more responsefulfillment constraints within the limits of guiding laws andregulations.

According to other embodiments, an example of Fulfillment ConstraintData 106 related to the identities of one or more Requestors 112includes a customer history associated with the data subjects. Thecustomer history may include one or more spending characteristics of theone or more Requestors 112, as well as any complaint history of the oneor more Requestors 112. For example, the spending characteristics orother applicable relationship that a Requestor 112 has with the companymay be a factor in determining whether the company fulfills the DSAR 102at no cost even though not legally obligated to do so, fulfills the DSAR102 for a processing fee, or denies the DSAR 102. In one embodiment, ifa second or subsequent DSAR 102 is received from a Requestor 112 withina threshold period of time (e.g., within a year of the first DSAR 102),then the company may determine that it is worth expending the necessaryresources to fulfill the DSAR 102 at no cost, even though not legallyrequired to do so, because the Requestor 112 is a good customer or holdsa particular standing or status recognized by the company. In makingthis determination, the DSAR Processing and Fulfillment Server 170 maydetermine if the one or more spending characteristics of the Requestor112 includes an amount spent over a reference time period that exceeds aspending threshold. If so, for example, the DSAR Processing andFulfillment Server 170 may fulfill the DSAR 102 after requesting one ormore processing fees.

Similar to a purchase history, a complaint history may be valuableFulfillment Constraint Data 106 utilized by the system to determine howor if to respond to the DSAR 102. For example, it may be beneficial tofulfill a second or subsequent DSAR 102 from a Requestor 112 that hasnever submitted a complaint or bad review of the company during asubstantial period of time even though that subsequent DSAR 102 does notlegally require a response at no cost. Conversely, it may be determinedthat the benefits of fulfilling a subsequent DSAR 102 at no cost from aperson with an extensive complaint history outweigh the costs of denyingor charging a fee for the request. It should be appreciated that anyquantity and type of weighting and prioritization of FulfillmentConstraint Data 106 may be utilized in a decision to fulfill, fulfillwith limitations, or deny a DSAR 102. Regardless of the precise mannerin which the Fulfillment Constraint Data 106 is used by the DSARProcessing and Fulfillment Server 170 in determining the action to takeon the DSAR 102, the data used in the determination may be digitallyattached to the identity of the Requestor 112 and stored in the ThirdParty Repository Server 104 (or One or More Databases 140 or One or MoreThird Party Servers 160) as Fulfillment Constraint Data 106.

An example of Fulfillment Constraint Data 106 related to one or moreSources 114 of malicious DSAR 102 submissions includes a particulardomain and/or a particular IP address. If a requestor submits anexcessive quantity of DSARs 102 using the same computer, then the DSARProcessing and Fulfillment Server 170 may store the domain or IP addressassociated with those electronic submission as Fulfillment ConstraintData 106 to identify that domain or IP address as a Source 114 ofmalicious DSAR 102 submissions. In doing so, future DSARs 102originating from the domain or IP address stored as FulfillmentConstraint Data 106 will be identified by the DSAR Processing andFulfillment Server 170 as being malicious or potentially malicious.According to one embodiment, one or more particular domains or IPaddresses associated with a competitor of the company are stored asFulfillment Constraint Data 106 to identify that competitor's domain orIP address as a Source 114 of malicious DSAR 102 submissions. Asubsequent search by the DSAR Processing and Fulfillment Server 170 forFulfillment Constraint Data 106 associated with a DSAR 102 will resultin a determination that the DSAR 102 originated from a competitor, whichflags the submission as being potentially malicious.

Another example of Fulfillment Constraint Data 106 related to one ormore Sources 114 of malicious DSAR 102 submissions includes a geographiclocation or region from which the DSAR 102 is submitted. For example, ifthe DSAR 102 originates from a country or specific geographic regioncommonly affiliated with a terrorist or other organization that may spamrequests to disrupt the company's operation and response to validrequests, then that country or geographic region may be stored asFulfillment Constraint Data 106 that flags DSARs 102 originating fromthat country or geographic region as being malicious or potentiallymalicious.

Similarly, Fulfillment Constraint Data 106 may include identificationsof political groups or organizations, protesting groups or organizationsthat commonly protest or object to the operations of the company,religious groups or organizations, or any other group or organizationthat may have views, beliefs, or causes that are contrary to those ofthe company. Any DSARs 102 submitted by a Requestor 112 or a Source 114that may be affiliated with these groups or organizations may be flaggedas being malicious or potentially malicious.

Handling of DSARs that are flagged or otherwise identified as beingmalicious or potentially malicious may be guided by company policy,applicable laws, and/or regulations. According to various embodiments,if the DSAR 102 is subject to one or more response fulfillmentconstraints, as determined from the presence of applicable FulfillmentConstraint Data 106 associated with the request, then the DSARProcessing and Fulfillment Server 170 acts on the DSAR 102 according toOne or More Limitations 192. The One or More Limitations 192 may includea Fulfillment Action 180 or a Deny Action 190. The Fulfillment Action180 includes fulfilling the DSAR 102 conditional upon payment of aprocessing fee. The Deny Action 190 includes denying or rejecting theDSAR 102.

If the DSAR Processing and Fulfillment Server 170 acts on the DSAR 102according to One or More Limitations 192, then a Notification 194 isprovided to the requestor. According to various embodiments, theNotification 194 includes a reason for the One or More Limitations 192,such as the presence of one or more response fulfillment constraints.The Notification 194 may further provide the requestor of their right tocommunicate with a supervisory authority regarding the One or MoreLimitations 192, and inform the requestor of their right to a judicialremedy without delay. The Notification 194 may include any informationmandated by applicable law or regulations, or desired according tocompany policy.

In addition to providing the Notification 194 to the requestor uponacting on the DSAR 102 according to One or More Limitations 192, theDSAR Processing and Fulfillment Server 170 may store or identifySupporting Documents 118 in the Third Party Repository Server 104.Judicial or other review actions taken by a supervisory authority afterthe denial of a DSAR 102, or fulfillment requiring a payment of aprocessing fee, may require documentation that identifies the applicableFulfillment Constraint Data 106 and supports the associated responsefulfillment constraints. In this situation, the Third Party RepositoryServer 104 provides a central storage location for the SupportingDocuments 118. It should be appreciated that the Supporting Documents118 may include links or locations to the electronic or physicaldocumentation stored in locations outside of the Third Party RepositoryServer 104 (e.g., One or More Databases 140 or One or More Third PartyServers 160).

FIG. 51 illustrates a routine 5100 for responding to a data subjectaccess request 102. A processor 202 associated with the DSAR Processingand Fulfillment Server 170 may perform this process. The routine 5100begins at operation 5102, where the DSAR Processing and FulfillmentServer 170 receives a DSAR 102. At operation 5104, the DSAR Processingand Fulfillment Server 170 validates the identity of the Requestor 112in the manner described above. The DSAR Processing and FulfillmentServer 170 determines at operation 5106 whether the DSAR 102 is subjectto response fulfillment constraints. As discussed in detail above, thisoperation may include searching for Fulfillment Constraint Data 106 in aThird Party Repository Server 104 or other database, server, orcombination thereof.

If the DSAR Processing and Fulfillment Server 170 does not findapplicable Fulfillment Constraint Data 106, then the routine 5100proceeds from operation 5106 to operation 5108, where the DSARProcessing and Fulfillment Server 170 takes a Fulfillment Action 180 andprocesses or fulfills the DSAR 102 and the routine 5100 ends. However,if at operation 5106, the DSAR Processing and Fulfillment Server 170finds applicable Fulfillment Constraint Data 106, then the routine 5100proceeds from operation 5106 to operation 5110, where the DSARProcessing and Fulfillment Server 170 provides a Notification 194 to theRequestor 112 and ensures Supporting Documents 118 are properly storedor indexed to support the One or More Limitations 192 imposed on theDSAR 102. At operation 5112, the DSAR Processing and Fulfillment Server170 takes the appropriate action according to the One or MoreLimitations 192 and the process 5100 ends. As discussed above, the Oneor More Limitations 192 may result in the DSAR 102 being fulfilled afterpayment of a processing fee, or a Deny Action 190.

Turning now to FIG. 52, a routine 5200 for responding to a data subjectaccess request while maintaining fulfillment constraint data will bediscussed according to particular embodiments. The routine 5200 beginsat operation 5202, where the DSAR Processing and Fulfillment Server 170stores Fulfillment Constraint Data 106 in One or More Databases 140, Oneor More Third Party Servers 160, or a Third Party Repository Server 104.The Fulfillment Constraint Data 106 may be associated with a Requestor112, a Source 114 of a DSAR 102, or any Other Fulfillment ConstraintData Criteria 116 related to the DSAR 102. At operation 5204, the DSARProcessing and Fulfillment Server 170 receives a DSAR 102. At operation5206, the DSAR Processing and Fulfillment Server 170 retrievesFulfillment Constraint Data 106 related to the DSAR 102 and takes actionbased on the DSAR 102 and the Fulfillment Constraint Data 106 atoperation 5208. As previously discussed, the action may includefulfilling the request, denying the request, or fulfilling the requestafter payment of a processing fee. Finally, at operation 5210, theFulfillment Constraint Data 106 is updated to reflect the current DSAR102 and associated information related to the Requestor 112 and Source114, and the routine 5200 ends.

Returning now to FIG. 4, FIG. 4 depicts a queue of pending data subjectaccess requests. As shown in this figure, the first three listed datasubject access requests are new and require verification beforeprocessing and fulfillment can begin. As shown in this figure, a user(e.g., such as a privacy officer or other privacy controller) may selecta particular request, and select an indicia for verifying the request.The user may also optionally select to reject the request. FIG. 5depicts an authentication window that enables the user to authenticate aparticular request. In various embodiments, the user may provide anexplanation of why the user is authenticating the request (e.g., becausethe requestor successfully completed on or more out-of-wallet questionsor for any other suitable reason). The user may further submit one ormore attachments to support the verification. In this way, the systemmay be configured to document that the authentication process wasperformed for each request (e.g., in case there was an issue withimproperly fulfilling a request, the company could show that they arefollowing procedures to prevent such improper processing). In otherembodiments, the system may enable the user to provide similar supportwhen rejecting a request (e.g., because the requestor was blacklisted,made excessive requests, etc.).

Data Subject Access Request Fulfillment Cost Determination

In various embodiments, as may be understood in light of thisdisclosure, fulfilling a data subject access request may be particularlycostly. In some embodiments, a company may store data regarding aparticular data subject in multiple different locations for a pluralityof different reasons as part of a plurality of different processing andother business activities. For example, a particular data subject may beboth a customer and an employee of a particular company or organization.Accordingly, in some embodiments, fulfilling a data subject accessrequest for a particular data subject may involve a plurality ofdifferent information technology (IT) professionals in a plurality ofdifferent departments of a particular company or organization. As such,it may be useful to determine a cost of a particular data subject accessrequest (e.g., particularly because, in some cases, a data subject isentitled to a response to their data subject access request as a matterof right at no charge).

In particular embodiments, in response to receiving a data subjectaccess request, the system may be configured to: (1) assign the requestto at least one privacy team member; (2) identify one or more IT teamsrequired to fulfill the request (e.g., one or more IT teams associatedwith one or more business units that may store Personal Data 108 relatedto the request); (3) delegate one or more subtasks of the request toeach of the one or more IT teams; (4) receive one or more time logs fromeach individual involved in the processing and fulfillment of the datasubject access request; (5) calculate an effective rate of eachindividual's time (e.g., based at least in part on the individual'ssalary, bonus, benefits, chair cost, etc.); (6) calculate an effectivecost of fulfilling the data subject access request based at least inpart on the one or more time logs and effective rate of each of theindividual's time; and (7) apply an adjustment to the calculatedeffective cost that accounts for one or more external factors (e.g.,overhead, etc.) in order to calculate a cost of fulfilling the datasubject access request.

In particular embodiments, the system is configured to substantiallyautomatically track an amount of time spent by each individual involvedin the processing and fulfillment of the data subject access request.The system may, for example, automatically track an amount of timebetween each individual opening and closing a ticket assigned to them aspart of their role in processing or fulfilling the data subject accessrequest. In other embodiments, the system may determine the time spentbased on an amount of time provided by each respective individual (e.g.,the individual may track their own time and submit it to the system).

In various embodiments, the system is configured to measure a cost ofeach particular data subject access request received, and analyze one ormore trends in costs of, for example: (1) data subject access requestsover time; (2) related data subject access requests; (3) etc. Forexample, the system may be configured to track and analyze cost andtime-to-process trends for one or more social groups, one or morepolitical groups, one or more class action groups, etc. In particular,the system may be configured to identify a particular group from whichthe system receives particularly costly data subject access request(e.g., former and/or current employees, members of a particular socialgroup, members of a particular political group, etc.).

In particular embodiments, the system may be configured to utilize datasubject access request cost data when processing, assigning, and/orfulfilling future data subject access requests (e.g., from a particularidentified group, individual, etc.). For example, the system may beconfigured to prioritize requests that are expected to be less costlyand time-consuming (e.g., based on past cost data) over requestsidentified as being likely more expensive. Alternatively, the system mayprioritize more costly and time-consuming requests over less costly onesin the interest of ensuring that the system is able to respond to eachrequest in a reasonable amount of time (e.g., within a time required bylaw, such as a thirty-day period, or any other suitable time period).Moreover, the cost data associated with processing, assigning, and/orfulfilling data subject access requests may be a factor utilized by theDSAR Processing and Fulfillment Server 170 in determining whether todeny a DSAR 102 or request a processing fee prior to fulfilling a DSAR102 after determining that the DSAR 102 is subject to one or moreresponse fulfillment constraints, as discussed above.

Customer Satisfaction Integration with Data Subject Access Requests

In various embodiments, the system may be configured to collect customersatisfaction data, for example: (1) as part of a data subject accessrequest submission form; (2) when providing one or more results of adata subject access request to the data subject; or (3) at any othersuitable time. In various embodiments, the customer satisfaction datamay be collected in the form of a suitable survey, free-form responsequestionnaire, or other suitable satisfaction data collection format(e.g., thumbs up vs. thumbs down, etc.).

FIG. 6 depicts an exemplary customer satisfaction survey that may beincluded as part of a data subject access request form, provided alongwith the results of a data subject access request, provided in one ormore messages confirming receipt of a data subject access request, etc.As shown in the figure, the customer satisfaction survey may relate tohow likely a customer (e.g., a data subject) is to recommend the company(e.g., to which the data subject has submitted the request) to a friend(e.g., or colleague). In the example shown in FIG. 6, the satisfactionsurvey may relate to a Net Promoter score (NPS), which may indicate aloyalty of a company's customer relationships. Generally speaking, theNet Promoter Score may measure a loyalty that exists between a providerand a consumer. In various embodiments, the provider may include acompany, employer, or any other entity. In particular embodiments, theconsumer may include a customer, employee, or other respondent to an NPSsurvey.

In particular embodiments, the question depicted in FIG. 6 is theprimary question utilized in calculating a Net Promoter Score (e.g.,“how likely is it that you would recommend our company/product/serviceto a friend or colleague?”). In particular embodiments, the question ispresented with responses ranging from 0 (not at all likely) to 10(extremely likely). In particular embodiments, the question may includeany other suitable scale. As may be understood from FIG. 6, the systemmay be configured to assign particular categories to particular ratingson the 10-point scale. The system may be configured to track and storeresponses provided by consumers and calculate an overall NPS score forthe provider. The system may be further configured to generate a visualrepresentation of the NPS score, including a total number of responsesreceived for each particular score and category as shown in FIG. 6.

In various embodiments, the system may be configured to measure datarelated to any other suitable customer satisfaction method (e.g., inaddition to NPS). By integrating a customer satisfaction survey with thedata subject access request process, the system may increase a number ofconsumers that provide one or more responses to the customersatisfaction survey. In particular embodiments, the system is configuredto require the requestor to respond to the customer satisfaction surveyprior to submitting the data subject access request.

Exemplary Technical Platforms

As will be appreciated by one skilled in the relevant field, the presentinvention may be, for example, embodied as a computer system, a method,or a computer program product. Accordingly, various embodiments may takethe form of an entirely hardware embodiment, an entirely softwareembodiment, or an embodiment combining software and hardware aspects.Furthermore, particular embodiments may take the form of a computerprogram product stored on a computer-readable storage medium havingcomputer-readable instructions (e.g., software) embodied in the storagemedium. Various embodiments may take the form of web-implementedcomputer software. Any suitable computer-readable storage medium may beutilized including, for example, hard disks, compact disks, DVDs,optical storage devices, and/or magnetic storage devices.

Various embodiments are described below with reference to block diagramsand flowchart illustrations of methods, apparatuses (e.g., systems), andcomputer program products. It should be understood that each block ofthe block diagrams and flowchart illustrations, and combinations ofblocks in the block diagrams and flowchart illustrations, respectively,can be implemented by a computer executing computer programinstructions. These computer program instructions may be loaded onto ageneral-purpose computer, special-purpose computer, or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions which execute on the computer or other programmabledata processing apparatus to create means for implementing the functionsspecified in the flowchart block or blocks.

These computer program instructions may also be stored in acomputer-readable memory that can direct a computer or otherprogrammable data processing apparatus to function in a particularmanner such that the instructions stored in the computer-readable memoryproduce an article of manufacture that is configured for implementingthe function specified in the flowchart block or blocks. The computerprogram instructions may also be loaded onto a computer or otherprogrammable data processing apparatus to cause a series of operationalsteps to be performed on the computer or other programmable apparatus toproduce a computer implemented process such that the instructions thatexecute on the computer or other programmable apparatus provide stepsfor implementing the functions specified in the flowchart block orblocks.

Accordingly, blocks of the block diagrams and flowchart illustrationssupport combinations of mechanisms for performing the specifiedfunctions, combinations of steps for performing the specified functions,and program instructions for performing the specified functions. Itshould also be understood that each block of the block diagrams andflowchart illustrations, and combinations of blocks in the blockdiagrams and flowchart illustrations, can be implemented by specialpurpose hardware-based computer systems that perform the specifiedfunctions or steps, or combinations of special purpose hardware andother hardware executing appropriate computer instructions.

Example System Architecture

FIG. 7 is a block diagram of a data subject access request processingand fulfillment system 100 according to a particular embodiment. Invarious embodiments, the data subject access request processing andfulfillment system is part of a privacy compliance system (also referredto as a privacy management system), or other system, which may, forexample, be associated with a particular organization and be configuredto aid in compliance with one or more legal or industry regulationsrelated to the collection and storage of Personal Data 108.

As may be understood from FIG. 7, the data subject access requestprocessing and fulfillment system 100 includes one or more computernetworks 115, a Data Model Generation Server 110, a Data ModelPopulation Server 120, an Intelligent Identity Scanning Server 130, Oneor More Databases 140 or other data structures, one or more remotecomputing devices 150 (e.g., a desktop computer, laptop computer, tabletcomputer, smartphone, etc.), and One or More Third Party Servers 160. Inparticular embodiments, the one or more computer networks 115 facilitatecommunication between the Data Model Generation Server 110, Data ModelPopulation Server 120, Intelligent Identity Scanning Server 130, One orMore Databases 140, one or more remote computing devices 150 (e.g., adesktop computer, laptop computer, tablet computer, smartphone, etc.),One or More Third Party Servers 160, and DSAR Processing and FulfillmentServer 170. Although in the embodiment shown in FIG. 1, the Data ModelGeneration Server 110, Data Model Population Server 120, IntelligentIdentity Scanning Server 130, One or More Databases 140, one or moreremote computing devices 150 (e.g., a desktop computer, laptop computer,tablet computer, smartphone, etc.), One or More Third Party Servers 160,and DSAR Processing and Fulfillment Server 170 are shown as separateservers, it should be understood that in other embodiments, one or moreof these servers and/or computing devices may comprise a single server,a plurality of servers, one or more cloud-based servers, or any othersuitable configuration.

The one or more computer networks 115 may include any of a variety oftypes of wired or wireless computer networks such as the Internet, aprivate intranet, a public switch telephone network (PSTN), or any othertype of network. The communication link between The Intelligent IdentityScanning Server 130 and the One or More Third Party Servers 160 may be,for example, implemented via a Local Area Network (LAN) or via theInternet. In other embodiments, the One or More Databases 140 may bestored either fully or partially on any suitable server or combinationof servers described herein.

FIG. 8 illustrates a diagrammatic representation of a computer 200 thatcan be used within the data subject access request processing andfulfillment system 100, for example, as a client computer (e.g., one ormore remote computing devices 150 shown in FIG. 7), or as a servercomputer (e.g., Data Model Generation Server 110, Data Model PopulationServer 120, Intelligent Identity Scanning Server 130, One or More ThirdParty Servers 160, and DSAR Processing and Fulfillment Server 170 shownin FIG. 7). In particular embodiments, the computer 200 may be suitablefor use as a computer within the context of the data subject accessrequest processing and fulfillment system 100 that is configured togenerate a data model and map one or more relationships between one ormore pieces of data that make up the model.

In particular embodiments, the computer 200 may be connected (e.g.,networked) to other computers in a LAN, an intranet, an extranet, and/orthe Internet. As noted above, the computer 200 may operate in thecapacity of a server or a client computer in a client-server networkenvironment, or as a peer computer in a peer-to-peer (or distributed)network environment. The computer 200 may be a personal computer (PC), atablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), acellular telephone, a web appliance, a server, a network router, aswitch or bridge, or any other computer capable of executing a set ofinstructions (sequential or otherwise) that specify actions to be takenby that computer. Further, while only a single computer is illustrated,the term “computer” shall also be taken to include any collection ofcomputers that individually or jointly execute a set (or multiple sets)of instructions to perform any one or more of the methodologiesdiscussed herein.

An exemplary computer 200 includes a processing device 202, a mainmemory 204 (e.g., read-only memory (ROM), flash memory, dynamic randomaccess memory (DRAM) such as synchronous DRAM (SDRAM) or Rambus DRAM(RDRAM), etc.), static memory 206 (e.g., flash memory, static randomaccess memory (SRAM), etc.), and a data storage device 218, whichcommunicate with each other via a bus 232.

The processing device 202 represents one or more general-purposeprocessing devices such as a microprocessor, a central processing unit,or the like. More particularly, the processing device 202 may be acomplex instruction set computing (CISC) microprocessor, reducedinstruction set computing (RISC) microprocessor, very long instructionword (VLIW) microprocessor, or processor implementing other instructionsets, or processors implementing a combination of instruction sets. Theprocessing device 202 may also be one or more special-purpose processingdevices such as an application specific integrated circuit (ASIC), afield programmable gate array (FPGA), a digital signal processor (DSP),network processor, or the like. The processing device 202 may beconfigured to execute processing logic 226 for performing variousoperations and steps discussed herein.

The computer 200 may further include a network interface device 208. Thecomputer 200 also may include a video display unit 210 (e.g., a liquidcrystal display (LCD) or a cathode ray tube (CRT)), an alphanumericinput device 212 (e.g., a keyboard), a cursor control device 214 (e.g.,a mouse), and a signal generation device 216 (e.g., a speaker).

The data storage device 218 may include a non-transitorycomputer-accessible storage medium 230 (also known as a non-transitorycomputer-readable storage medium or a non-transitory computer-readablemedium) on which is stored one or more sets of instructions (e.g.,software instructions 222) embodying any one or more of themethodologies or functions described herein. The software instructions222 may also reside, completely or at least partially, within mainmemory 204 and/or within processing device 202 during execution thereofby computer 200—main memory 204 and processing device 202 alsoconstituting computer-accessible storage media. The softwareinstructions 222 may further be transmitted or received over a network115 via network interface device 208.

While the computer-accessible storage medium 230 is shown in anexemplary embodiment to be a single medium, the term“computer-accessible storage medium” should be understood to include asingle medium or multiple media (e.g., a centralized or distributeddatabase, and/or associated caches and servers) that store the one ormore sets of instructions. The term “computer-accessible storage medium”should also be understood to include any medium that is capable ofstoring, encoding or carrying a set of instructions for execution by thecomputer and that cause the computer to perform any one or more of themethodologies of the present invention. The term “computer-accessiblestorage medium” should accordingly be understood to include, but not belimited to, solid-state memories, optical and magnetic media, etc.

Systems for Managing Data Subject Access Requests

In various embodiments, the system may include a ticket managementsystem and/or other systems for managing data subject access requests.Various embodiments of such systems are described below.

Overview

Ticket management systems, according to various embodiments, are adaptedto receive data subject access requests (DSAR's) from particular datasubjects, and to facilitate the timely processing of valid DSAR's by anappropriate respondent. In particular embodiments, the ticket managementsystem receives DSAR's via one or more webforms that each may beaccessed via an appropriate link on a respective web page. In otherembodiments, the system may receive DSAR's through any other suitablemechanism, such as via a computer software application (e.g., amessaging application such as Slack, Twitter), or through entry by arepresentative who may receive the information, for example, viasuitable paper forms or over the phone.

The ticket management system may include a webform creation tool that isadapted to allow a user to create customized webforms for receivingDSAR's from various different data subject types and for routing therequests to appropriate individuals for processing. The webform creationtool may, for example, allow the user to specify the language that theform will be displayed in, what particular information is to berequested for the data subject and/or provided by the data subject, whoany DSAR's that are received via the webform will be routed to, etc. Inparticular embodiments, after the user completes their design of thewebform, the webform creation tool generates code for the webform thatmay be cut and then pasted into a particular web page.

The system may be further adapted to facilitate processing of DSAR'sthat are received via the webforms, or any other suitable mechanism. Forexample, the ticket management system may be adapted to execute one ormore of the following steps for each particular DSAR received via thewebforms (or other suitable mechanism) described above: (1) beforeprocessing the DSAR, confirm that the DSAR request was actuallysubmitted by the particular data subject of the DSAR (or, for example,by an individual authorized to make the DSAR request on the datasubject's behalf, such as a parent, guardian, power-of-attorney holder,etc.)—any suitable method may be used to confirm the identity of theentity/individual submitting the DSAR—for example, if the systemreceives the DSAR via a third-party computer system, the system mayvalidate authentication via API secret, or by requiring a copy of one ormore particular legal documents (e.g., a particular contract between twoparticular entities)—the system may validate the identity of anindividual by, for example, requiring the individual (e.g., datasubject) to provide particular account credentials, by requiring theindividual to provide particular out-of-wallet information, throughbiometric scanning of the individual (e.g., finger or retinal scan), orvia any other suitable identity verification technique; (2) if the DSARwas not submitted by the particular data subject, deny the request; (3)if the DSAR was submitted by the particular data subject, advance theprocessing of the DSAR; (4) route the DSAR to the correct individual(s)or groups internally for handling; (5) facilitate the assignment of theDSAR to one or more other individuals for handling of one or moreportions of the DSAR; and/or (6) facilitate the suspension of the datasubject access request. In particular embodiments, the system mayperform any one or more of the above steps automatically. The systemthen generates a receipt for the DSAR request that the user can use fora transactional record of their submitted request.

In particular embodiments, the ticket management system may be adaptedto generate a graphical user interface (e.g., a DSAR request-processingdashboard) that is adapted to allow a user (e.g., a privacy officer ofan organization that is receiving the DSAR) to monitor the progress ofany the DSAR requests. The GUI interface may display, for each DSAR, forexample, an indication of how much time is left (e.g., quantified indays and/or hours) before a legal and/or internal deadline to fulfillthe request. The system may also display, for each DSAR, a respectiveuser-selectable indicium that, when selected, may facilitate one or moreof the following: (1) verification of the request; (2) assignment of therequest to another individual; (3) requesting an extension to fulfillthe request; (4) rejection of the request; or (5) suspension of therequest.

As noted immediately above, and elsewhere in this application, inparticular embodiments, any one or more of the above steps may beexecuted by the system automatically. As a particular example, thesystem may be adapted to automatically verify the identity of the DSARrequestor and then automatically fulfill the DSAR request by, forexample, obtaining the requested information via a suitable data modeland communicating the information to the requestor. As anotherparticular example, the system may be configured to automatically routethe DSAR to the correct individual for handling based at least in parton one or more pieces of information provided (e.g., in the webform).

Operation of Example Implementation

FIGS. 9-49 are screen shots that demonstrate the operation of aparticular embodiment. FIGS. 9-12 show a graphical user interface (GUI)of an example webform construction tool. FIG. 9 shows a user working todesign a webform called “Web_form_1”. As may be understood from thevertical menu shown on the left-hand side of the screen, the webformconstruction tool allows users to design a webform by: (1) specifyingthe details of the form (via the “Form Details” tab); (2) defining thefields that will be displayed on the webform (via the “Webform Fields”tab); (3) defining the styling of the webform (via the “Form Styling”tab); and (4) defining various settings associated with the webform (viathe “Settings” tab). As shown in FIGS. 10-12, the user may also specifytext to be displayed on the webform (e.g., via a “Form Text” tab).

FIG. 10 shows that, by selecting the “Form Details” tab, the user maydefine which answers a requestor will be able to specify on the webformin response to prompts for information regarding what type of individualthey are (customer, employee, etc.) and what type of request they aremaking via the webform. Example request types include: (1) a request forall Personal Data 108 that an organization is processing for the datasubject (a copy of the Personal Data 108 in a commonly used,machine-readable format); (2) a request for all such Personal Data 108to be deleted; (3) a request to update Personal Data 108 that theorganization is storing for the data subject; (4) a request to opt outof having the organization use the individual's personal information inone or more particular ways (e.g., per the organization's standardbusiness practices); (5) file a complaint; and/or (6) other.

FIG. 11 shows that, by selecting the “Settings” tab, the user mayspecify various system settings, such as whether Captcha will be used toverify that information is being entered by a human, rather than acomputer.

FIG. 12 shows that, by selecting the Form Styling tab, the user mayspecify the styling of the webform. The styling may include, forexample: (1) a header logo; (2) header height; (3) header color; (4)body text color; (5) body text size; (6) form label color; (7) buttoncolor; (8) button text color; (9) footer text color; (10) footer textsize; and/or any other suitable styling related to the webform.

In other embodiments, the system is configured to enable a user tospecify, when configuring a new webform, what individual at a particularorganization (e.g., company) will be responsible for responding torequests made via the webform. The system may, for example, enable theuser to define a specific default sub-organization (e.g., within theorganization) responsible for responding to DSAR's submitted via the newwebform. As such, the system may be configured to automatically route anew DSAR made via the new webform to the appropriate sub-organizationfor processing and fulfillment. In various embodiments, the system isconfigured to route one or more various aspects of the DSAR to one ormore different sub-organizations within the organization.

In still other embodiments, the system is configured to enable a usergenerating webforms to assign multiple webforms to multiple differentsuborganizations within an organization. For example, an organizationcalled ACME, Inc. may have a website for each of a plurality ofdifferent brands (e.g., sub-organizations) under which ACME sellsproducts (e.g., UNICORN Brand T-shirts, GRIPP Brand Jeans, etc.). As maybe understood in light of this disclosure, each website for each of theparticular brands may include an associated webform for submittingDSAR's. Each respective webform may be configured to route a DSAR madevia its associated brand website to a particular sub-organization withinACME for handling DSAR's related to the brand.

As noted above, after the user uses the webform construction tool todesign a particular webform for use on a particular web page, thewebform construction tool generates code (e.g., HTML code) that may bepasted into the particular web page to run the designed webform page.

FIG. 13 shows the privacy webpage of a company (e.g., the ACMEcorporation). As shown in this figure, a requestor may submit a DSAR byselecting a “Submit a Privacy Related Request” button on the web page.

FIG. 14 shows a webform that is displayed after a requestor selects the“Submit a Privacy Related Request” button on the privacy webpage of FIG.13. As may be understood from this figure, the requestor may completethe webform by specifying which type of user they are, and what type ofrequest they are making. The webform also asks the requestor to provideenough personal information to confirm their identity (e.g., and fulfillthe request). As shown in this figure, the system may prompt a usersubmitting a DSAR to provide information such as, for example: (1) whattype of requestor the user is (e.g., employee, customer, etc.); (2) whatthe request involves (e.g., requesting info, opting out, deleting data,updating data, etc.); (3) first name; (4) last name; (5) email address;(6) telephone number; (7) home address; (8) one or more other pieces ofidentifying information; and/or (9) one or more details associated withthe request. FIG. 15 shows an example populated version of the webform.

As shown in FIG. 16, after a requestor completes the webform and selectsa “submit” indicia, the system displays a message to the requestorindicating that their DSAR has been successfully submitted. The systemalso displays a Request ID associated with the request. In response tothe requestor successfully submitting the request, the system may alsosend an email to the requestor confirming the request. An example of asuitable confirmation email is shown in FIG. 17.

In various embodiments, the system includes a dashboard that may be usedby various individuals within an organization (e.g., one or more privacyofficers of an organization) to manage multiple DSAR requests. Asdiscussed above, the dashboard may display DSAR's submitted,respectively, to a single organization, any of multiple differentsub-organizations (divisions, departments, subsidiaries etc.) of aparticular organization, and/or any of multiple independentorganizations. For example, the dashboard may display DSAR's that weresubmitted from a parent organization and from the parent organization'sU.S. and European subsidiaries. This may be advantageous, for example,because it may allow an organization to manage all DSAR requests of allof its sub-organizations centrally.

FIGS. 18-29, 31-33, 35-40, and 45-47 depict various exampleuser-interface screens of a DSAR request-management dashboard. As may beunderstood from FIG. 18, after an appropriate user (e.g., a privacyofficer associated with a particular organization) logs into the system,the system may display a Data Subject Request Queue that may, forexample, display a listing of all data subject access requests that theappropriate individual has been designated to process. As shown in FIG.18, each data subject access request may be represented by a respectiverow of information that includes: (1) an ID number for the request; (2)the name of the data subject who has submitted the request; (3) thestatus of the request; (4) the number of days that are left to respondto the request (e.g., according to applicable laws and/or internalprocedures); (5) an indication as to whether the deadline to respond tothe request has been extended; (6) a creation date of the request; (7)an indication of the type of requestor that submitted the request(customer, employee, etc.); (8) the name of the individual who has beenassigned to process the request (e.g., the respondent). This screen mayalso include selectable “Edit” and “Filter” buttons that respectivelyfacilitate acting on and filtering the various requests displayed on thepage.

As shown in FIG. 19, in response to a respondent selecting the editbutton, the system displays a dropdown menu allowing the respondent toselect between taking the following actions: (1) verify the request; (2)assign the request to another individual; (3) request an extension; (4)reject the request; or (5) suspend the request.

FIGS. 20 and 21 show a message that the system displays to therespondent in response to the respondent selecting the “verify” option.As shown in this figure, the system prompts the respondent to indicatewhether they are sure that they wish to authenticate the request. Thesystem also presents an input field where the respondent can enter textto be displayed to the requestor along with a request for the requestorto provide information verifying that they are the data subjectassociated with the request. After the respondent populates the inputfield, they may submit the request by selecting a “Submit” button.

In other embodiments, the input field may enable the respondent toprovide one or more supporting reasons for a decision, by therespondent, to authenticate the request. The respondent may also uploadone or more supporting documents (such as an attachment). The supportingdocuments or information may include, for example, one or more documentsutilized in confirming the requestor's identity, etc.

In response to the respondent selecting the Submit button, the systemchanges the status of the request to “In Progress” and also changes thecolor of the request's status from orange to blue (or to any othersuitable color)—see FIG. 22. The system also generates and sends amessage (e.g., an electronic or paper message) to the requestor askingthem to submit information verifying the request. The message mayinclude the text that the respondent entered in the text box of FIGS. 20and 21.

As shown in FIGS. 23-25, in response to a respondent selecting the“Edit” button and then selecting the “Assign” indicia from the displayeddropdown menu, the system displays a Request Assignment interface thatallows a respondent to indicate who the request should be assigned to.For example, the respondent may indicate that they will be handling therequest, or assign the request to another suitable individual, who may,for example, then be designated as the respondent for the request. Ifthe respondent assigns the request to another individual, they may alsoprovide an email address or other correspondence information for theindividual. The Request Assignment interface includes a comment box forallowing a respondent to add a message to the individual that theassignment will be assigned to regarding the assignment. In response tothe respondent selecting the “Assign” button, the system assigns therequest to the designated individual for handling. If the request hasbeen assigned to another individual, the system automatically generatesand sends a message (e.g., an electronic message such as an email or SMSmessage) to the individual informing them of the assignment.

As shown in FIGS. 26-28, in response to a respondent selecting the“Edit” button and then selecting the “Reject” indicia from the displayeddropdown menu, the system displays a Reject Request interface. Thisinterface includes a comment box for allowing a respondent to add amessage to the requestor as to why the request was rejected. In responseto the respondent selecting the “Submit” button, the system changes thestatus of the request to “Rejected” and changes the color of therequest's status indicator to red (See FIG. 29). The system may alsoautomatically generate a message (e.g., an electronic or paper message)to the requestor notifying them that their request has been rejected anddisplaying the text that the respondent entered into the Reject Requestinterface of FIG. 28. An example of such a message is shown in FIG. 30.

As shown in FIGS. 31-32, in response to a respondent selecting the“Edit” button and then selecting the “Request Extension” indicia fromthe displayed dropdown menu, the system displays a Request Extensioninterface. This includes a text box for allowing a user to indicate thenumber of days for which they would like to extend the current deadlinefor responding to the request. For example, the dialog box of FIG. 32shows the respondent requesting that the current deadline be extended by90 days. In response to the respondent entering a desired extensionduration and selecting the “Submit” button, the system updates thedeadline in the system's memory (e.g., in an appropriate data structure)to reflect the extension. For instance, in the example of FIG. 32, thesystem extends the deadline to be 90 days later than the currentdeadline. As shown in FIG. 33, the system also updates the “Days Left toRespond” field within the Data Subject Request Queue to reflect theextension (e.g., from 2 days from the current date to 92 days from thecurrent date). As shown in FIG. 34, the system may also generate anappropriate message (e.g., an electronic or paper message) to therequestor indicating that the request has been delayed. This message mayprovide a reason for the delay and/or an anticipated updated completiondate for the request.

In particular embodiments, the system may include logic forautomatically determining whether a requested extension complies withone or more applicable laws or internal policies and, in response,either automatically grant or reject the requested extension. Forexample, if the maximum allowable time for replying to a particularrequest is 90 days under the controlling laws and the respondentrequests an extension that would result in the fulfillment of therequest 91 or more days from the date that the request was submitted,the system may automatically reject the extension request. In variousembodiments, the system may also communicate, to the respondent (e.g.,via a suitable electronic message or text display on a system userinterface) an explanation as to why the extension request was denied,and/or a maximum amount of time (e.g., a maximum number of days) thatthe deadline may be extended under the applicable laws or policies. Invarious embodiments, if the system determines that the requestedextension is permissible under the applicable laws and/or policies, thesystem may automatically grant the extension. In other embodiments, thesystem may be configured to automatically modify a length of therequested extension to conform with one or more applicable laws and/orpolicies.

As shown in FIGS. 35-40, a respondent may obtain additional detailsregarding a particular request by selecting (e.g., clicking on) therequest on the Data Subject Request Queue screen. For example, FIG. 36shows a Data Subject Request Details screen that the system displays inresponse to a respondent selecting the “Donald Blair” request on theuser interface screen of FIG. 35. As shown in FIG. 36, the Data SubjectRequest Details screen shows all correspondence between the organizationand the requesting individual regarding the particular data subjectaccess request. As may be understood from FIG. 37, when a respondentselects a particular correspondence (e.g., email), the system displaysthe correspondence to the respondent for review or other processing.

As shown in FIG. 38, in various embodiments, the system may provide aselectable “Reply” indicia that allows the respondent to reply toparticular correspondence from an individual. As may be understood fromthis figure, in response to the respondent selecting the “Reply”indicia, the system may display a dropdown menu of various standardreplies. For example, the dropdown menu may provide the option ofgenerating a reply to the requestor indicating that the request has beenrejected, is pending, has been extended, or that the request has beencompleted.

As shown in FIG. 39, in response to the respondent selecting “Reply asCompleted”, the system may display a draft email to the requestorexplaining that the request has been completed. The respondent may thenedit this email and send the correspondence (e.g., via email) to therequestor by selecting a “Send as Complete” indicia. As shown in FIG.40, the system may, in response, display an indicator adjacent thecorrespondence indicating that the correspondence included a replyindicating that the request was complete. This may be useful in allowingindividuals to understand the contents of the correspondence withouthaving to open it.

FIG. 41 shows an example email automatically generated by the system inresponse to the respondent selecting “Reply as Completed” on the screenshown in FIG. 38. As shown in FIG. 41, the correspondence may include asecure link that the requestor may select to access the data that wasrequested in the DSAR. In particular embodiments, the link is a link toa secure website, such as the website shown in FIG. 42, that providesaccess to the requested data (e.g., by allowing a user to download a.pdf file, or other suitable file, that includes the requested data). Asshown in FIG. 42, the website may require multiple pieces of data toverify that the requestor is permitted to access the site. For example,in order to access the website, the requestor may be required to provideboth the unique ID number of the request, and an authentication token,which the system may send to the user via email—See FIGS. 43 and 44.

FIGS. 45-49 are computer screen shots that depict additional userinterfaces according to various embodiments.

Additional Concepts

Automated Data Subject Verification

In various embodiments, before a data subject request can be processed,the data subject's identity needs to be verified. In variousembodiments, the system provides a mechanism to automatically detect thetype of authentication required for a particular data subject based onthe type of Data Subject Access Request being made and automaticallyissues a request to the data subject to verify their identity againstthat form of identification. For example, a subject rights request mightonly require two types of authentication, but a deletion request mayrequire four types of data to verify authentication. The system mayautomatically detect which is type of authentication is required basedon the DSAR and send an appropriate request to the data subject toverify their identity.

Intelligent Prioritization of DSAR's

In various embodiments, the system may be adapted to prioritize theprocessing of DSAR's based on metadata about the data subject of theDSAR. For example, the system may be adapted for: (1) in response toreceiving a DSAR, obtaining metadata regarding the data subject; (2)using the metadata to determine whether a priority of the DSAR should beadjusted based on the obtained metadata; and (3) in response todetermining that the priority of the DSAR should be adjusted based onthe obtained metadata, adjusting the priority of the DSAR.

Examples of metadata that may be used to determine whether to adjust thepriority of a particular DSAR include: (1) the type of request, (2) thelocation from which the request is being made, (3) current sensitivitiesto world events, (4) a status of the requestor (e.g., especially loyalcustomer), or (5) any other suitable metadata.

In various embodiments, in response to the system determining that thepriority of a particular DSAR should be elevated, the system mayautomatically adjust the deadline for responding to the DSAR. Forexample, the system may update the deadline in the system's memoryand/or modify the “Days Left to Respond” field (See FIG. 19) to includea fewer number of days left to respond to the request. Alternatively, orin addition, the system may use other techniques to convey to arespondent that the request should be expedited (e.g., change the colorof the request, send a message to the respondent that they shouldprocess the request before non-prioritized requests, etc.)

In various embodiments, in response to the system determining that thepriority of a particular DSAR should be lowered, the system mayautomatically adjust the deadline for responding to the DSAR by addingto the number of days left to respond to the request.

Automatic Deletion of Data Subject Records Based on Detected Systems

In particular embodiments, in response a data subject submitting arequest to delete their Personal Data 108 from an organization'ssystems, the system may: (1) automatically determine where the datasubject's Personal Data 108 is stored; and (2) in response todetermining the location of the data (which may be on multiple computingsystems), automatically facilitate the deletion of the data subject'sPersonal Data 108 from the various systems (e.g., by automaticallyassigning a plurality of tasks to delete data across multiple businesssystems to effectively delete the data subject's Personal Data 108 fromthe systems). In particular embodiments, the step of facilitating thedeletion may comprise, for example: (1) overwriting the data in memory;(2) marking the data for overwrite; (2) marking the data as free (e.g.,and deleting a directory entry associated with the data); and/or (3) anyother suitable technique for deleting the Personal Data 108. Inparticular embodiments, as part of this process, the system uses anappropriate data model (see discussion above) to efficiently determinewhere all of the data subject's Personal Data 108 is stored.

Automatic Determination of Business Processes that Increase Chance ofDeletion Requests

In various embodiments, the system is adapted to store, in memory, a logof DSAR actions. The system may also store, in memory, additionalinformation regarding the data subjects of each of the requests. Thesystem may use this information, for example, to determine whichbusiness processes are most commonly associated with a data subjectsubmitting a request to have their personal information deleted from theorganization's systems. The organization may then use this informationto revise the identified business processes in an effort to reduce thenumber of deletion requests issued by data subjects associated with thebusiness processes.

As a particular example, the system may analyze stored information todetermine that a high number (e.g., 15%) of all participants in acompany's loyalty program submit requests to have their personalinformation deleted from the company's systems. In response to makingthis determination, the system may issue an electronic alert to anappropriate individual (e.g., a privacy officer of the company),informing them of the high rate of members of the company's loyaltyprogram issuing Personal Data 108 delete requests. This alert may promptthe individual to research the issue and try to resolve it.

CONCLUSION

Although embodiments above are described in reference to various privacycompliance monitoring systems, it should be understood that variousaspects of the system described above may be applicable to otherprivacy-related systems, or to other types of systems, in general.

While this specification contains many specific embodiment details,these should not be construed as limitations on the scope of anyinvention or of what may be claimed, but rather as descriptions offeatures that may be specific to particular embodiments of particularinventions. Certain features that are described in this specification inthe context of separate embodiments may also be implemented incombination in a single embodiment. Conversely, various features thatare described in the context of a single embodiment may also beimplemented in multiple embodiments separately or in any suitablesub-combination. Moreover, although features may be described above asacting in certain combinations and even initially claimed as such, oneor more features from a claimed combination may in some cases be excisedfrom the combination, and the claimed combination may be directed to asub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems maygenerally be integrated together in a single software product orpackaged into multiple software products.

Many modifications and other embodiments of the invention will come tomind to one skilled in the art to which this invention pertains havingthe benefit of the teachings presented in the foregoing descriptions andthe associated drawings. Therefore, it is to be understood that theinvention is not to be limited to the specific embodiments disclosed andthat modifications and other embodiments are intended to be includedwithin the scope of the appended claims. Although specific terms areemployed herein, they are used in a generic and descriptive sense onlyand not for the purposes of limitation.

What is claimed is:
 1. A computer-implemented data processing method forresponding to a data subject access request, the method comprising:receiving, by one or more computer processors, the data subject accessrequest from a requestor comprising one or more request parameters,wherein the one or more request parameters comprise one or more piecesof personal data associated with the requestor; validating, by the oneor more computer processors, the requestor based at least in part on theone or more request parameters; at least partially in response tovalidating the requestor, determining, by the one or more computerprocessors, based at least in part on fulfillment constraint data,whether the data subject access request is subject to one or moreresponse fulfillment constraints associated with the requestor, whereindetermining whether the data subject access request is subject to theone or more response fulfillment constraints comprises determiningwhether the data subject access request comprises one of a thresholdquantity of data subject access requests from the requestor within athreshold time period; at least partially in response to determiningthat the data subject access request is subject to the one or moreresponse fulfillment constraints, determining, by the one or morecomputer processors, based at least in part on historical dataassociated with the requestor, whether to fulfill the data subjectaccess request; at least partially in response to determining, based atleast in part on the historical data associated with the requestor, notto fulfill the data subject access request, taking, by the one or morecomputer processors, one or more actions selected from a group ofactions comprising: (a) denying the data subject access request; and (b)requesting, from the requestor, one or more processing fees prior tofulfilling the request; at least partially in response to determining,based at least in part on the historical data associated with therequestor, to fulfill the data subject access request, fulfilling, bythe one or more computer processors, the data subject access request;and at least partially in response to determining that the data subjectaccess request is not subject to the one or more response fulfillmentconstraints, fulfilling, by the one or more computer processors, thedata subject access request.
 2. The computer-implemented data processingmethod of claim 1, wherein the historical data associated with therequestor comprises a rating associated with the requestor.
 3. Thecomputer-implemented data processing method of claim 1, wherein thehistorical data associated with the requestor comprises one or morepieces of data selected from a group of pieces of data consisting of:(a) one or more spending characteristics of the requestor; (b) one ormore complaint characteristics of the requestor; and (c) a status of therequestor.
 4. The computer-implemented data processing method of claim3, wherein: the historical data associated with the requestor comprisesthe one or more spending characteristics of the requestor; and the oneor more spending characteristics of the requestor comprises an amount ofmoney spent by the requestor over a particular time period.
 5. Thecomputer-implemented data processing method of claim 4, whereindetermining, based at least in part on the historical data associatedwith the requestor, whether to fulfill the data subject access requestcomprises determining, by the one or more computer processors, whetherthe amount of money spent by the requestor over the particular timeperiod exceeds a threshold.
 6. The computer-implemented data processingmethod of claim 1, wherein the threshold time period comprises a singleday.
 7. The computer-implemented data processing method of claim 1,wherein the historical data associated with the requestor comprises acurrent or former employment status of the requestor.
 8. Anon-transitory computer-readable medium storing computer-executableinstructions for responding to a data subject access request by:receiving, by one or more computer processors, the data subject accessrequest from a source of the data subject access request comprising oneor more request parameters, wherein the one or more request parameterscomprise one or more pieces of personal data associated with arequestor; identifying, by the one or more computer processors, therequestor based at least in part on the one or more request parameters;at least partially in response to identifying the requestor,determining, by the one or more computer processors, based at least inpart on fulfillment constraint data, whether the data subject accessrequest is subject to one or more response fulfillment constraintsassociated with the requestor, wherein determining whether the datasubject access request is subject to the one or more responsefulfillment constraints comprises determining whether the data subjectaccess request comprises one of a threshold quantity of data subjectaccess requests from the requestor within a threshold time period; atleast partially in response to determining that the data subject accessrequest is subject to the one or more response fulfillment constraints,determining, by the one or more computer processors, based at least inpart on historical data associated with the requestor, whether tofulfill the data subject access request; at least partially in responseto determining, based at least in part on the historical data associatedwith the requestor, not to fulfill the data subject access request:notifying, by the one or more computer processors, the requestor thatthe data subject access request is subject to one or more limitations;and taking, by the one or more computer processors, one or more actionsselected from a group of actions consisting of: (a) denying the datasubject access request; and (b) requesting, from the requestor, one ormore processing fees prior to fulfilling the request; at least partiallyin response to determining, based at least in part on the historicaldata associated with the requestor, to fulfill the data subject accessrequest, fulfilling, by the one or more computer processors, the datasubject access request; and updating the fulfillment constraint data, bythe one or more computer processors in a computer memory, to reflectthat the data subject access request was received.
 9. The non-transitorycomputer-readable medium of claim 8, wherein: the one or more requestparameters comprise one or more pieces of source data; and thecomputer-executable instructions further comprise instructions foridentifying, by the one or more computer processors, the source of thedata subject access request based at least in part on the one or morepieces of source data.
 10. The non-transitory computer-readable mediumof claim 9, wherein the one or more response fulfillment constraints areassociated with the source of the data subject access request.
 11. Thenon-transitory computer-readable medium of claim 10, wherein the sourceof the data subject access request is selected from a group consistingof: (a) a particular IP address; (b) a particular domain; and (c) aparticular geographical region.
 12. The non-transitory computer-readablemedium of claim 8, wherein the historical data associated with therequestor comprises one or more pieces of data selected from a group ofpieces of data consisting of: (a) one or more spending characteristicsof the requestor; (b) one or more complaint characteristics of therequestor; and (c) a status of the requestor.
 13. The non-transitorycomputer-readable medium of claim 12, wherein: the historical dataassociated with the requestor comprises the one or more complaintcharacteristics of the requestor; and the one or more complaintcharacteristics of the requestor comprises a number of complaintsreceived from the requestor over a particular time period.
 14. Thenon-transitory computer-readable medium of claim 13, whereindetermining, based at least in part on the historical data associatedwith the requestor, whether to fulfill the data subject access requestcomprises determining, by the one or more computer processors, that thenumber of complaints received from the requestor over the particulartime period is zero.
 15. A system for processing data subject accessrequests, the system comprising: one or more computer processors; and acomputer memory comprising a non-transitory computer-readable mediumthat stores computer-executable instructions for processing data subjectaccess requests that, when executed by the one or more computerprocessors, cause the one or more computer processors to performoperations comprising: receiving, by the one or more computerprocessors, a data subject access request from a requestor comprisingone or more request parameters, wherein the one or more requestparameters comprise one or more pieces of personal data associated withthe requestor; validating, by the one or more computer processors, therequestor based at least in part on the one or more request parameters;at least partially in response to validating the requestor, determining,by the one or more computer processors, based at least in part onfulfillment constraint data, whether the data subject access request issubject to one or more response fulfillment constraints associated withthe requestor, wherein the one or more response fulfillment constraintscomprise a threshold quantity of data subject access requests from therequestor within a threshold time period; at least partially in responseto determining that the data subject access request is subject to theone or more response fulfillment constraints, determining, by the one ormore computer processors, that a quantity of data subject accessrequests received from the requestor within the threshold period of timeexceeds the threshold quantity of data subject access requests; at leastpartially in response to determining that the quantity of data subjectaccess requests received from the requestor within the threshold periodof time exceeds the threshold quantity of data subject access requests,determining, by the one or more computer processors, based at least inpart on historical data associated with the requestor, whether tofulfill the data subject access request; at least partially in responseto determining, based at least in part on the historical data associatedwith the requestor, not to fulfill the data subject access request,taking, by the one or more computer processors, one or more actionscomprising: (a) denying the data subject access request; (b) notifyingthe requestor that the data subject access request is subject to one ormore limitations; and (c) requesting, from the requestor, one or moreprocessing fees prior to fulfilling the request; at least partially inresponse to determining, based at least in part on the historical dataassociated with the requestor, to fulfill the data subject accessrequest, fulfilling, by the one or more computer processors, the datasubject access request; and at least partially in response todetermining that the data subject access request is not subject to theone or more response fulfillment constraints, fulfilling, by the one ormore computer processors, the data subject access request.
 16. Thesystem of claim 15, wherein the historical data associated with therequestor comprises one or more pieces of data selected from a group ofpieces of data consisting of: (a) one or more spending characteristicsof the requestor; (b) one or more complaint characteristics of therequestor; and (c) a status of the requestor.
 17. The system of claim16, wherein: the historical data associated with the requestor comprisesthe one or more complaint characteristics of the requestor; and the oneor more complaint characteristics of the requestor comprises a number ofcomplaints received from the requestor over a particular time period.18. The system of claim 17, wherein determining, based at least in parton the historical data associated with the requestor, whether to fulfillthe data subject access request comprises determining, by the one ormore computer processors, that the number of complaints received fromthe requestor over the particular time period is associated with anextensive complaint history for the requestor.
 19. The system of claim16, wherein: the historical data associated with the requestor comprisesthe status of the requestor; and the status of the requestor comprisesan indication that the requestor is associated with a competitor of anentity receiving the data subject access request.
 20. The system ofclaim 15, wherein the operations further comprise updating, by the oneor more computer processors in the computer memory, the historical dataassociated with the requestor to reflect that the data subject accessrequest was received.